Modulations of neuronal network interactions by seizure precursors are only partially understood and difficult to measure, in part due to inherent intra- and inter-patient seizure heterogeneity and EEG variability. This study investigated preictal neuromodulations associated with seizures originating in the temporal and/or frontal lobes, using information theoretic parameters estimated from awake scalp EEGs in two frequency ranges, ≤100 Hz and >100 Hz, respectively. Seizure-related activity at high frequencies has not been extensively estimated in awake scalp EEGs. Based on the statistical similarity of preictal and ictal information parameters, preictal network interactions appeared to be specifically modulated at frequencies >100 Hz, but not at lower frequencies. The dynamics of these parameters varied distinctly according to the origin of seizure onset (temporal versus frontal). Although preliminary, and based on a small patient sample for which the potential heterogeneity of multiple anticonvulsive medications was difficult to control, these results suggest that preictal modulations may be estimated from high-frequency scalp EEGs using directional information measures with high specificity to ictal events, and may thus be promising for improving seizure prediction.
Baseline neurodynamics are believed to play an important role in normal brain function. A potentially intrinsic property of the brain is the weak coupling between networks at rest, which enables it to be flexible, adapt, process novel stimuli, and learn. Brain regions become differentially coordinated in response to cognitive task and behavior demands and external stimuli. However, abnormally synchronized resting brain networks may also be associated with different pathologies. We investigated baseline network dynamics in the epileptic brain using information theoretic parameters to quantify coupling and directionality of information flow between different cortical regions. We estimated relative entropy, conditional mutual information and a related measure of directional coupling, from EEGs of patients with epilepsy and healthy subjects. At rest, the healthy brain appears to be characterized by low and non-directional network coupling, whereas the epileptic brain appears to be transiently and directionally synchronized.
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